1edd71a2c1
Phase C.5a-fixup — completes C.5a's additive infrastructure so C.5b can be
a true atomic contract flip with zero scaffolding work mixed in:
- Allocate dh_aux1_pre_scratch [B_max, AUX_TRUNK_H1=256] +
dh_aux2_pre_scratch [B_max, AUX_TRUNK_H2=128] (missed in C.5a — both
required by aux_trunk_backward.launch per gpu_aux_trunk.rs:266-267).
- Collector struct gains 6× u64 aux_trunk_{w1,b1,w2,b2,w3,b3}_ptr fields,
exp_aux_trunk_forward_ops: AuxTrunkForwardOps field (constructed in
ctor on collector's stream), and set_trainer_aux_trunk_param_ptrs
setter — mirrors the existing set_trainer_params_ptr zero-copy pattern.
- Trainer gains aux_trunk_param_ptrs() -> (u64×6) accessor returning
raw_ptr() for all 6 aux trunk parameter tensors.
- training_loop wires the new setter at both existing
set_trainer_params_ptr call sites (initial fused-ctx init + fold-boundary
re-init).
NO contract change: wire sites still call save_h_s2. The setter is called
and the 6 aux trunk param ptrs are populated, but no collector-side launch
reads them yet — C.5b atomically inserts aux_trunk_forward.launch(...)
post-forward_online_f32 and switches the aux head input pointer.
Graph-capture audit: aux_heads_backward IS INSIDE the captured `forward`
child graph (call chain: submit_forward_ops_main → launch_cublas_backward
→ launch_cublas_backward_to → aux_heads_backward; capture begins at
fused_training.rs:2964 / capture_child_graph). The existing function body
is fully device-side (zero host writes) — capture-safe by construction.
C.5b's new aux_trunk Adam launch is also fully device-side and will sit
inside the same captured region. The host writes for aux_trunk_t_pinned
must use the existing GPU-side increment_step_counters kernel chain
(submit_counters_ops, line 22799) — NOT host-side aux_trunk_adam_step
+= 1 inside capture. ISV-driven LR/clip writes happen pre-capture
(cold-path); the captured graph reads via aux_trunk_lr_dev_ptr /
aux_trunk_grad_clip_dev_ptr. This avoids the &self → &mut self ripple on
aux_heads_backward (gap 4 in C.5b implementer's blocker report). Full
wiring strategy + alternative (pre-capture host-write) documented in
docs/dqn-wire-up-audit.md C.5a-fixup section.
Verification:
- cargo check -p ml --tests --all-targets: clean (no new warnings).
- cargo test -p ml --test aux_trunk_oracle_tests --test sp14_oracle_tests
--release -- --ignored --nocapture: 12/12 pass (8 aux_trunk + 4 sp14;
bit-identical to C.5a baseline — pure scaffolding, no regression).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Foxhunt
Production HFT trading system in Rust.
Architecture
The workspace contains 32 crates organized as follows:
Core Libraries (16)
| Crate | Purpose |
|---|---|
trading_engine |
Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing |
risk |
VaR, Kelly, circuit breakers, kill switches, compliance |
risk-data |
Risk data types and shared structures |
trading-data |
Trading data types |
ml |
DQN Rainbow, PPO, TFT, Mamba2, ensemble inference |
ml-data |
ML data types and feature definitions |
data |
Market data ingestion and storage |
backtesting |
Replay engine, strategy tester |
adaptive-strategy |
Ensemble execution, microstructure analysis |
common |
Shared types, resilience, error handling |
storage |
S3 and local model storage |
model_loader |
Model serialization and loading |
market-data |
Market data feed handlers |
database |
PostgreSQL access layer (SQLx) |
config |
Configuration management |
tli |
CLI commands and tooling |
Services (8)
| Service | Purpose |
|---|---|
backtesting_service |
gRPC backtesting service |
broker_gateway_service |
FIX routing, broker connectivity |
trading_service |
Core trading operations |
ml_training_service |
Model training orchestration |
data_acquisition_service |
Market data acquisition |
trading_agent_service |
Autonomous trading agents |
api_gateway |
gRPC API gateway with auth |
web-gateway |
Axum REST + WebSocket gateway |
Frontend
web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.
Building
# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace
# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib
# Clippy
SQLX_OFFLINE=true cargo clippy --workspace
ML Models
Four production model architectures on Candle v0.9.1 with CUDA:
- DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
- PPO -- Proximal Policy Optimization with GAE and LSTM policies
- TFT -- Temporal Fusion Transformer for multi-horizon forecasting
- Mamba2 -- State space model for sequence prediction
Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.
Infrastructure
- Git: Gitea at
git.fxhnt.ai(Tailscale-only), Scaleway DEV1-S - Observability: OpenTelemetry OTLP (env
OTEL_EXPORTER_OTLP_ENDPOINT) - Database: PostgreSQL with SQLx offline mode for CI
License
Proprietary. All rights reserved.